Markov random field on region adjacency graph for the fusion of SAR and optical data in radargrammetric applications

Florence Tupin, Michel Roux

Research output: Contribution to journalArticlepeer-review

Abstract

This paper deals with the estimation of an elevation model using a pair of synthetic aperture radar (SAR) images and an optical image in semiurban areas. The proposed method is based on a Markovian regularization of an elevation field defined on a region adjacency graph (RAG). This RAG is obtained by oversegmenting the optical image. The support for elevation hypotheses is given by the structural matching of features extracted from both SAR images. The regularization model takes into account discontinuities of buildings thanks to an implicit edge process. Starting from a good initialization, optimization is obtained through an iterated conditional mode algorithm.

Original languageEnglish
Pages (from-to)1920-1928
Number of pages9
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume43
Issue number8
DOIs
Publication statusPublished - 1 Aug 2005

Keywords

  • High-resolution synthetic aperture radar (SAR) images
  • Markov random field (MRF)
  • Radargrammetry
  • Three-dimensional reconstruction
  • Urban areas

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